scholarly journals Tuning radiative heat flows between interior surfaces and human occupants to improve heating and cooling efficiency

2020 ◽  
Author(s):  
Aaswath Raman ◽  
Jin Xu
Keyword(s):  
Thermal Comfort ◽  
Energy Use ◽  
Energy Savings ◽  
Weather Conditions ◽  
Cold Weather ◽  
Set Point ◽  
Heating And Cooling ◽  
Building Surfaces ◽  
Interior Walls ◽  
High Emissivity

Space heating and cooling in buildings account for nearly 20% of energy use globally. In most buildings this energy is used to maintain the thermal comfort of the building’s human occupants by maintaining the interior air temperature at a particular set point. However, if one could maintain the human occupant’s thermal comfort while decreasing the heating or increasing the cooling set point, dramatic energy savings are possible. Here, we propose and evaluate an untapped degree of freedom in improving building efficiency: dynamically tuning the thermal emissivity of interior building surfaces at long-wave infrared wavelengths to maintain thermal comfort. We show that in cold weather conditions tuning the emissivity of interior walls, floors and ceilings to a low value (0.1) can decrease the set point temperature as much as 7°C, corresponding to an energy saving of nearly 67.7% relative to high emissivity materials (0.9). Conversely, in warm weather, high emissivity interior surfaces result in a 38.5% energy savings relative to low emissivity surfaces, highlighting the need for tunability for maximal year-round efficiency. Our results reveal the remarkable energy savings potential possible by better controlling the ubiquitous flows of heat that surround us in the form of thermal radiation.

scholarly journals Tuning radiative heat flows between interior surfaces and human occupants to improve heating and cooling efficiency

2020 ◽  
Author(s):  
Jin Xu ◽  
Aaswath Raman
Keyword(s):  
Thermal Comfort ◽  
Energy Use ◽  
Energy Savings ◽  
Weather Conditions ◽  
Cold Weather ◽  
Set Point ◽  
Heating And Cooling ◽  
Building Surfaces ◽  
Interior Walls ◽  
High Emissivity

Space heating and cooling in buildings account for nearly 20% of energy use globally. In most buildings this energy is used to maintain the thermal comfort of the building’s human occupants by maintaining the interior air temperature at a particular set point. However, if one could maintain the human occupant’s thermal comfort while decreasing the heating or increasing the cooling set point, dramatic energy savings are possible. Here, we propose and evaluate an untapped degree of freedom in improving building efficiency: dynamically tuning the thermal emissivity of interior building surfaces at long-wave infrared wavelengths to maintain thermal comfort. We show that in cold weather conditions tuning the emissivity of interior walls, floors and ceilings to a low value (0.1) can decrease the set point temperature as much as 7°C, corresponding to an energy saving of nearly 67.7% relative to high emissivity materials (0.9). Conversely, in warm weather, high emissivity interior surfaces result in a 38.5% energy savings relative to low emissivity surfaces, highlighting the need for tunability for maximal year-round efficiency. Our results reveal the remarkable energy savings potential possible by better controlling the ubiquitous flows of heat that surround us in the form of thermal radiation.

scholarly journals Tuning radiative heat flows between interior surfaces and human occupants to improve heating and cooling efficiency

2020 ◽  
Author(s):  
Jin Xu ◽  
Aaswath Raman
Keyword(s):  
Thermal Comfort ◽  
Energy Use ◽  
Energy Savings ◽  
Weather Conditions ◽  
Cold Weather ◽  
Set Point ◽  
Heating And Cooling ◽  
Building Surfaces ◽  
Interior Walls ◽  
High Emissivity

Space heating and cooling in buildings account for nearly 20% of energy use globally. In most buildings this energy is used to maintain the thermal comfort of the building’s human occupants by maintaining the interior air temperature at a particular set point. However, if one could maintain the human occupant’s thermal comfort while decreasing the heating or increasing the cooling set point, dramatic energy savings are possible. Here, we propose and evaluate an untapped degree of freedom in improving building efficiency: dynamically tuning the thermal emissivity of interior building surfaces at long-wave infrared wavelengths to maintain thermal comfort. We show that in cold weather conditions tuning the emissivity of interior walls, floors and ceilings to a low value (0.1) can decrease the set point temperature as much as 7°C, corresponding to an energy saving of nearly 67.7% relative to high emissivity materials (0.9). Conversely, in warm weather, high emissivity interior surfaces result in a 38.5% energy savings relative to low emissivity surfaces, highlighting the need for tunability for maximal year-round efficiency. Our results reveal the remarkable energy savings potential possible by better controlling the ubiquitous flows of heat that surround us in the form of thermal radiation.

scholarly journals Impacts on Indoor Thermal Comfort and Heating Energy Use in Hellenic Dwellings from Occupant Behavioral Reactions

2021 ◽  
Vol 11 (14) ◽  
pp. 6254
Author(s):  
Elena G. Dascalaki ◽  
Constantinos A. Balaras
Keyword(s):  
Thermal Comfort ◽  
Energy Use ◽  
Energy Savings ◽  
Local Heating ◽  
Economic Recession ◽  
Heating System ◽  
Building Stock ◽  
Heating Systems ◽  
Indoor Thermal Comfort ◽  
Energy Audits

In an effort to reduce the operational cost of their dwellings, occupants may even have to sacrifice their indoor thermal comfort conditions. Following the economic recession in Greece over recent years, homeowners have been forced to adapt their practices by shortening heating hours, lowering the indoor thermostat settings, isolating spaces that are not heated or even turning off their central heating system and using alternative local heating systems. This paper presents the results from over 100 occupant surveys using questionnaires and walk-through energy audits in Hellenic households that documented how occupants operated the heating systems in their dwellings and the resulting indoor thermal comfort conditions and actual energy use. The results indicate that the perceived winter thermal comfort conditions were satisfactory in only half of the dwellings, since the actual operating space heating periods averaged only 5 h (compared with the assumed 18 h in standard conditions), while less than half heated their entire dwellings and only a fifth maintained an indoor setpoint temperature of 20 °C, corresponding to standard comfort conditions. Mainstream energy conservation measures include system maintenance, switching to more efficient systems, reducing heat losses and installing controls. This information is then used to derive empirical adaptation factors for bridging the gap between the calculated and actual energy use, making more realistic estimates of the expected energy savings following building renovations, setting prudent targets for energy efficiency and developing effective plans toward a decarbonized building stock.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.

scholarly journals Comparison Evaluations of VRF and RTU Systems Performance on Flexible Research Platform

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Je-hyeon Lee ◽  
Piljae Im ◽  
Jeffrey D. Munk ◽  
Mini Malhotra ◽  
Min-seok Kim ◽  
...  
Keyword(s):  
Energy Use ◽  
Energy Savings ◽  
Thermal Conditions ◽  
The United States ◽  
Energy Performance ◽  
Coefficient Of Performance ◽  
Part Load ◽  
Variable Air Volume ◽  
Heating And Cooling ◽  
Load Conditions

The energy performance of a variable refrigerant flow (VRF) system was evaluated using an occupancy-emulated research building in the southeastern region of the United States. Full- and part-load performance of the VRF system in heating and cooling seasons was compared with a conventional rooftop unit (RTU) variable-air-volume system with electric resistance heating. During both the heating and cooling seasons, full- and part-load conditions (i.e., 100%, 75%, and 50% thermal loads) were maintained alternately for 2 to 3 days each, and the energy use, thermal conditions, and coefficient of performance (COP) for the RTU and VRF system were measured. During the cooling season, the VRF system had an average COP of 4.2, 3.9, and 3.7 compared with 3.1, 3.0, and 2.5 for the RTU system under 100%, 75%, and 50% load conditions and resulted in estimated energy savings of 30%, 37%, and 47%, respectively. During the heating season, the VRF system had an average COP ranging from 1.2 to 2.0, substantially higher than the COPs of the RTU system, and resulted in estimated energy savings of 51%, 47%, and 27% under the three load conditions, respectively.

scholarly journals The Derivation of Cooling Set-Point Temperature in an HVAC System, Considering Mean Radiant Temperature

2019 ◽  
Vol 11 (19) ◽  
pp. 5417
Author(s):  
Jinmog Han ◽  
Jongkyun Bae ◽  
Jihoon Jang ◽  
Jumi Baek ◽  
Seung-Bok Leigh
Keyword(s):  
Thermal Comfort ◽  
Indoor Environment ◽  
Thermal Characteristics ◽  
Weather Conditions ◽  
System Control ◽  
Hvac System ◽  
Mean Radiant Temperature ◽  
Point Temperature ◽  
Set Point ◽  
Radiant Temperature

Heating, ventilation, and air-conditioning (HVAC) systems usually have a set-point temperature control feature that uses the indoor dry-bulb temperature to control the indoor environment. However, an incorrect set-point temperature can reduce thermal comfort and result in unnecessary energy consumption. This study focuses on a derivation method for the optimal cooling set-point temperature of an HVAC system used in office buildings, considering the thermal characteristics and daily changes in the weather conditions, to establish a comfortable indoor environment and minimize unnecessary energy consumption. The operative temperature is used in the HVAC system control, and the mean radiant temperature is predicted with 94% accuracy through a multiple regression analysis by applying the indoor thermal environment data and weather information. The regression equation was utilized to create an additional equation to calculate the optimal set-point temperature. The simulation results indicate that the HVAC system control with the new set-point temperatures calculated from the derived equation improves thermal comfort by 38.5% (26%p). This study confirmed that a cooling set-point temperature that considers both the thermal characteristics of a building and weather conditions is effective in enhancing the indoor thermal comfort during summer.

scholarly journals Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5396
Author(s):  
Christina Turley ◽  
Margarite Jacoby ◽  
Gregory Pavlak ◽  
Gregor Henze
Keyword(s):  
Thermal Comfort ◽  
Energy Use ◽  
Energy Savings ◽  
Prediction Models ◽  
Smart Devices ◽  
Building Energy Efficiency ◽  
Occupancy Models ◽  
Probabilistic Prediction ◽  
Hvac Control ◽  
Occupancy Prediction

Occupancy-aware heating, ventilation, and air conditioning (HVAC) control offers the opportunity to reduce energy use without sacrificing thermal comfort. Residential HVAC systems often use manually-adjusted or constant setpoint temperatures, which heat and cool the house regardless of whether it is needed. By incorporating occupancy-awareness into HVAC control, heating and cooling can be used for only those time periods it is needed. Yet, bringing this technology to fruition is dependent on accurately predicting occupancy. Non-probabilistic prediction models offer an opportunity to use collected occupancy data to predict future occupancy profiles. Smart devices, such as a connected thermostat, which already include occupancy sensors, can be used to provide a continually growing collection of data that can then be harnessed for short-term occupancy prediction by compiling and creating a binary occupancy prediction. Real occupancy data from six homes located in Colorado is analyzed and investigated using this occupancy prediction model. Results show that non-probabilistic occupancy models in combination with occupancy sensors can be combined to provide a hybrid HVAC control with savings on average of 5.0% and without degradation of thermal comfort. Model predictive control provides further opportunities, with the ability to adjust the relative importance between thermal comfort and energy savings to achieve savings between 1% and 13.3% depending on the relative weighting between thermal comfort and energy savings. In all cases, occupancy prediction allows the opportunity for a more intelligent and optimized strategy to residential HVAC control.

scholarly journals Optimization of building form and its fenestration in response to microclimate conditions of an urban area

2020 ◽  
Vol 172 ◽  
pp. 19002
Author(s):  
Kavan Javanroodi ◽  
Vahid M. Nik ◽  
Yuchen Yang
Keyword(s):  
Thermal Comfort ◽  
Urban Area ◽  
Urban Areas ◽  
Energy Demand ◽  
High Performance ◽  
Weather Conditions ◽  
Climate Data ◽  
Heating And Cooling ◽  
Building Form ◽  
Microclimate Conditions

Designing building form in urban areas is a complicated process that demands considering a high number of influencing parameters. On the other hand, there has been an increasing trend to design highly fenestrated building envelopes for office buildings to induce higher levels of natural lighting into the workspace. This paper presents a novel optimization framework to design high-performance building form and fenestration configuration considering the impacts of urban microclimate in typical and extreme weather conditions during a thirty-year period of climate data (2010-2039). In this regard, based on the introduced technique and algorithm, the annual energy demand and thermal comfort of over 8008 eligible form combinations with eight different fenestration configurations and seven different building orientation angels were analysed in a detailed urban area to find optimal design solutions in response to microclimate conditions. Results showed that adopting the framework, annual heating, and cooling demand can be reduced by 21% and 38% while maintaining thermal comfort by taking design-based decisions at the early stages of design.

scholarly journals Self-Learning Algorithm to Predict Indoor Temperature and Cooling Demand from Smart WiFi Thermostat in a Residential Building

2020 ◽  
Vol 12 (17) ◽  
pp. 7110
Author(s):  
Kefan Huang ◽  
Kevin P. Hallinan ◽  
Robert Lou ◽  
Abdulrahman Alanezi ◽  
Salahaldin Alshatshati ◽  
...  
Keyword(s):  
Thermal Comfort ◽  
Energy Savings ◽  
Dynamic Models ◽  
Short Term Memory ◽  
Learning Algorithm ◽  
Peak Load ◽  
Back Propagation ◽  
Residential Building ◽  
Measured Temperature ◽  
Heating And Cooling

Smart WiFi thermostats have moved well beyond the function they were originally designed for; namely, controlling heating and cooling comfort in buildings. They are now also learning from occupant behaviors and permit occupants to control their comfort remotely. This research seeks to go beyond this state of the art by utilizing smart WiFi thermostat data in residences to develop dynamic predictive models for room temperature and cooling/heating demand. These models can then be used to estimate the energy savings from new thermostat temperature schedules and estimate peak load reduction achievable from maintaining a residence in a minimum thermal comfort condition. Back Propagation Neural Network (BPNN), Long-Short Term Memory (LSTM), and Encoder-Decoder LSTM dynamic models are explored. Results demonstrate that LSTM outperforms BPNN and Encoder-Decoder LSTM approach, yielding and a MAE error of 0.5 °C, equal to the resolution error of the measured temperature. Additionally, the models developed are shown to be highly accurate in predicting savings from aggressive thermostat set point schedules, yielding deep reduction of up to 14.3% for heating and cooling, as well as significant energy reduction from curtailed thermal comfort in response to a high demand event.

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